CLAMS: Bringing Quality to Data Lakes
Summary: CLAMS discovers and enforces expressive integrity constraints from lake data with limited schema, inferring schemas and constraints from RDF-like triples. It scales out, supports human-in-the-loop validation and repair, demonstrated on a real enterprise lake with 1.2B triples. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mina Farid
- 2. Alexandra Roatis
- 3. Ihab F. Ilyas
- 4. Hella-Franziska Hoffmann
- 5. Xu Chu
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 936 | Data Lake Management: Challenges and Opportunities | 2019 | VLDB | 0.00015197838 |
| 2,842 | Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning | 2023 | VLDB | 8.0366354e-05 |
| 3,001 | SANTOS: Relationship-based Semantic Table Union Search | 2023 | SIGMOD | 7.739698e-05 |
| 4,860 | Integrating Data Lake Tables | 2023 | VLDB | 5.867964e-05 |
| 7,384 | The VADA Architecture for Cost-Effective Data Wrangling | 2017 | SIGMOD | 4.7400209e-05 |
| 8,725 | OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs | 2023 | VLDB | 4.453957e-05 |
| 9,321 | READY: Completeness is in the Eye of the Beholder | 2017 | CIDR | 4.3517399e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 556 | Discovering Denial Constraints | 2013 | VLDB | 0.00020214701 |
| 5,671 | Descriptive and Prescriptive Data Cleaning | 2014 | SIGMOD | 5.3797808e-05 |
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| 5,470 | RetClean: Retrieval-Based Data Cleaning Using LLMs and Data Lakes | 2024 | VLDB | 5.4894925e-05 |
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| 3,283 | Constance: An Intelligent Data Lake System | 2016 | SIGMOD | 7.27606e-05 |
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| 1,481 | Automating Large-Scale Data Quality Verification | 2018 | VLDB | 0.00011715754 |